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. 2017 Mar 1;24(2):432-440.
doi: 10.1093/jamia/ocw119.

A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care

Clare L Brown  1   2 , Helen L Mulcaster  1 , Katherine L Triffitt  1 , Dean F Sittig  3 , Joan S Ash  4 , Katie Reygate  5 , Andrew K Husband  1 , David W Bates  6   7   8 , Sarah P Slight  1   2   6
Affiliations

A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care

Clare L Brown et al. J Am Med Inform Assoc. .

Abstract

Objective: To understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems.

Materials and methods: We conducted a systematic review of the literature published between January 2004 and June 2015 using three large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Studies that reported qualitative data about the types and causes of these errors were included. A narrative synthesis of all eligible studies was undertaken.

Results: A total of 1185 publications were identified, of which 34 were included in the review. We identified 8 key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, nonintuitive or inflexible ordering, repeat prescriptions and automated processes, users' work processes, and clinical decision support systems. Displaying an incomplete list of a patient's medications on the computer screen often contributed to prescribing errors. Lack of system flexibility resulted in users employing error-prone workarounds, such as the addition of contradictory free-text comments. Users' misinterpretations of how text was presented in CPOE systems were also linked with the occurrence of prescribing errors.

Discussion and conclusions: Human factors design is important to reduce error rates. Drop-down menus should be designed with safeguards to decrease the likelihood of selection errors. Development of more sophisticated clinical decision support, which can perform checks on free-text, may also prevent errors. Further research is needed to ensure that systems minimize error likelihood and meet users' workflow expectations.

Keywords: alerts; clinical decision support; computerized provider order entry; decision-making; medication errors; patient safety.

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Figures

Figure 1.
Figure 1.
Diagrammatic representation of the steps involved in the literature search.
See this image and copyright information in PMC

References

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